BUSINESS SCIENCE
Data Science Using Bare-Metal Servers?
The 5 arguments for “beyond the cloud”
There are 5 cases in which you may want to go bare(-metal) with your mission-critical data projects
Data Science on the cloud?
Cloud computing services are the future of data science, according to just about everyone. To suggest otherwise is practically blasphemy these days — and yet this mindset comes with some serious downsides. In fact, for start-ups and small companies, Cloud servers can be your ultimate downfall.
When I started my company Evo, I was all-in on the Cloud. After all, some of the same advances in computing that enabled Cloud services at a mass scale made Evo’s prescriptive AI possible. Leveraging Big Data in new ways is critical for transformative impact. Furthermore, we received free credits from Azure and AWS, which we love(d).
But as Evo scaled, the costs began to spiral out of control. Because of the many resources required by the many IO operations carried out by Evo data engineers, data scientists and deployed products, it cost Evo tens of thousands of dollars a month just for basic server needs.
